25 lines
922 B
Markdown
25 lines
922 B
Markdown
# Unit 1: Introduction to Data Mining
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Welcome to your simplified notes for Unit 1.
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## Table of Contents
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1. [[01_Introduction_to_Data_Mining|Introduction & DIKW Pyramid]]
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- What is Data Mining?
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- The DIKW Pyramid (Data, Information, Knowledge, Wisdom)
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2. [[02_Data_Mining_Process|The Data Mining Process]]
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- Steps from Goal Definition to Deployment
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- Issues in Data Mining (Privacy, Scalability)
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3. [[03_Data_Mining_Techniques|Techniques & Functionalities]]
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- Predictive vs Descriptive Mining
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- Classification, Regression, Clustering, Association Rules
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4. [[04_Data_Preprocessing|Data Preprocessing]]
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- Why do we need it?
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- Cleaning, Integration, Reduction, Transformation
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5. [[05_Data_Processing_Methods|Data Processing Methods]]
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- Manual vs Electronic
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- Batch, Real-time, Online Processing
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6. [[06_Data_Discretization|Data Discretization]]
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- Binning, Histograms
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- Concept Hierarchy
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